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Related Questions
- What is the process of fine-tuning pre-trained models, and how does it enable them to perform well on new tasks?
- How does fine-tuning affect the model's architecture, and what changes occur during the adaptation process?
- What are the key factors that influence the effectiveness of fine-tuning, and how can they be optimized?
- Can you explain the concept of transfer learning in the context of fine-tuning pre-trained models?
- How does fine-tuning pre-trained models help to adapt their language understanding and generation capabilities to new tasks?
- What are some common challenges or limitations of fine-tuning pre-trained models, and how can they be addressed?
- How does fine-tuning compare to other methods for adapting pre-trained models to new tasks, such as retraining from scratch or using task-specific models?
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